Machines shape the ‘golden ratio’ of data-driven business

Sep 13, 2017

This is the third in a series of three blog posts in which Niral Patel, MD of Oracle South Africa has been discussing the role people, data and machines must play in forming the data-driven businesses of tomorrow.
You can read part one, on the role of people, here http://it-online.co.za/2017/08/11/goldsmiths-at-the-heart-of-data-driven-business/ and part two on the role of data, here http://it-online.co.za/2017/08/24/how-data-driven-businesses-are-transforming-our-world/
Tim Berners-Lee, the inventor of the World Wide Web, had this to say in 2007 about how data should flow in a modern business: “Any enterprise CEO really ought to be able to ask a question that involves connecting data across the organisation, be able to run a company effectively, and especially to be able to respond to unexpected events. Most organisations are missing this ability to connect all the data together.”
Berners-Lee’s point was that the value of data is not being fully realised if it is sitting in silos and people are making decisions based only on a partial view of all the data that could be available to them. If businesses lack the people and the technology to bring data together for a more comprehensive view of their business and their opportunities, then its’ worth is a fraction of its potential value. This is why businesses need to aim for a ‘golden ratio’ of people, data and machines, where each is adding value and complementing the value of the other in harmony.
Technology’s role in this balancing act certainly cannot be underestimated. The ability to collect, collate and connect that data at scale simply did not exist until the onset of cloud computing which is breaking down the silos Berners-Lee was alluding to.
The connectivity that cloud provides across businesses, supply chains, customers, platforms, applications and databases means organisations can gain a single view of their operation. The power and flexibility of cloud means they can process unprecedented volumes of data at speed through cloud applications, platforms and infrastructure.
Cloud is also enabling machines to work more autonomously and to communicate with one another as we are seeing with the rise of technologies such as artificial intelligence (AI) and machine learning. Such technologies are bringing speed and scale to areas of the business that otherwise would be labour intensive and time-consuming processes.
For instance, retailers looking to improve customer experience and satisfaction are turning to the Internet of Things (IoT) and interconnected sensors spread through the supply chain to uncover new ways of increasing efficiency, reducing cost, improving product availability and providing more accurate product information.
In the back office, companies are experimenting with technology powered by AI and machine learning, such as self-service chatbots to improve the HR experience for employees. Rather than having to wait on HR to answer routine questions, workers can simply interact with a chatbot linked directly to the organisation’s HR systems that can answer many questions automatically. There is a clear business benefit here in addition to improved employee satisfaction — HR teams who spend less time on these admin tasks can focus on more projects that require their unique expertise.
But automation is certainly not about replacing employees with machines. Rather, it’s about speeding up tasks that take more time than businesses can afford to give to them as they seek to innovate at pace and achieve greater profitability through efficiency and by enabling people to focus on more valuable tasks. It is about improving the decision-making capabilities of people by arming them with a richness of highly relevant, topical and timely data that otherwise would not be possible to collect.
This is why it comes back to this idea of a ‘golden ratio’ of the right people, using the right data and machines in perfect balance. No business wants too many, or an unprofitable amount of either, but will always need all three in pursuit of data-driven success.